旱稻导入系碾磨品质和垩白粒率的QTL定位及其与土壤水分的互作分析

doi:10.3724/SP.J.1006.2009.00831

摘要/Abstract

摘要：

以优质水稻品种越富为遗传背景，具有旱稻品种IRAT109导入片段的271份导入系为材料，在水、旱田2个土壤水分环境下调查糙米率、精米率、整精米率和垩白粒率4个品质性状，研究旱田栽培对稻米品质性状的影响，进行QTL定位及基因型与环境的互作分析。结果表明，整精米率和垩白粒率易受土壤水分环境的影响，糙米率和精米率相对稳定。适当水分胁迫能提高稻米的整精米率，减少垩白粒率。利用混合线性模型，水、旱田条件下共检测到4个品质性状的10个加性QTL和2对上位性互作QTL，分别位于第3、4、7、8和9染色体。3个加性QTL (qMR9、qHMR7和qHMR9)和一对上位性互作QTL (qHMR3~qHMR9)的贡献率大于10%。7个QTL与前人研究结果相一致。第4染色体RM1112~RM1272和第9染色体RM1189~RM410是QTL集中分布的区域。根据不同性状对干旱胁迫的反应特点，分别选择水、旱田条件下贡献率大、稳定的QTL或者具有旱田特异性的QTL，进行标记辅助聚合育种是培育抗旱、优质稻的一个有效途径。

关键词: 稻米, 碾磨品质, 垩白粒率, QTL与环境互作, 导入系

Abstract:

Milling quality and percentage of chalky grain of rice (Oryza sativa L.) are important traits to producers and consumers. The objectives of this study were to characterize the response of brown rice (BR), milled rice (MR), head milled rice (HMR), and percentage of chalky grain (PCG) to upland water stress and to identify QTLs for the traits. A set of 271 introgression lines (ILs) (BC₅F₃), carrying segments from upland cultivar IRAT109 in the background of lowland rice cultivar Yuefu, were used, and data were collected under upland and lowland environments. Great changes were detected between upland and lowland conditions in head milled rice and percentage of chalky grain, but relative stability in brown rice and milled rice. Head milled rice increased and percentage of chalky grain significantly decreased under upland condition. A total of ten additive QTLs and two pairs of digenic epistatic interactions QTLs for BR, MR, HMR, and PCG were detected on chromosomes 3, 4, 7, 8, and 9. The contribution of single QTL ranged from 1.81 to 17.49%, three QTLs (qMR9, qHMR7, qHMR9) and one pairs of digenic epistatic interactions (qHMR3~qHMR9) accounted for above 10% of the phenotypic variation. Six QTLs were no significant QTL × Environment interaction effects, seven QTLs were the same with those from previous reports, and two genomic intervals, RM1112~RM1272 on chromosome 4 and RM1189~RM410 on chromosome 9, were cluster regions of the QTLs. These co-localized QTLs and common QTLs will facilitate marker-assisted selection for grain quality traits in rice breeding.

Key words: Rice, Milling quality, Percentage of chalky grain, QTL × Envirnment interaction, Introgression lines(ILs)

李俊周,付春阳,李自超. 旱稻导入系碾磨品质和垩白粒率的QTL定位及其与土壤水分的互作分析[J]. 作物学报, 2009, 35(5): 831-838.

LI Jun-Zhou,FU Chun-Yang,LI Zi-Chao. QTL Mapping and QTL × Environment Interactions of Milling Quality and Percentage of Chalky Grain in Upland Rice Introgression Lines under Upland and Lowland Environments[J]. Acta Agron Sin, 2009, 35(5): 831-838.

参考文献

[1]Shi C-H(石春海), He C-X(何慈信), Zhu J(朱军). Analysis of genetic effects and genotype × environment interactions for milling quality traits of rice. Acta Genet Sin (遗传学报), 1998, 25(1): 46–53 (in Chinese with English abstract)
[2]Guo Y-Y(郭银燕), Zhang Y-K(张云康), Chen R-X(陈润兴), Hu B-M(胡秉明), Chen K-R(陈昆荣). Analysis of genotype, test site, genotype × site effects on milling qualities of early seaon indica rice. Hereditas (遗传), 1997, 19(4): 12–16(in Chinese with English abstract)
[3]Gravoris K A, Moldenhauer K A K, Rohman P C. Genetic and genotype × environment effects for rough rice and head rice yields. Crop Sci, 1991, 31: 907–911
[4]Brown L R, Halweil B. China’s water shortage could shake world food security. World Watch, 1998, 7: 3–4
[5]Luo L-J(罗利军), Zhang Q-F(张启发). The status and strategy on drought resistance of rice (Oryza sativa L.). Chin J Rice Sci (中国水稻科学), 2001, 15(3): 209–214 (in Chinese with English abstract)
[6]Tan Y F, Xing Y Z, Li J X, Yu S B, Xu C G, Zhang Q F. Genetic bases of appearance quality of rice grains in Shanyou 63, an elite rice hybrid. Theor Appl Genet, 2000, 101: 823–829
[7]Mei H-W(梅捍卫), Luo L-J(罗利军), Guo L-B(郭龙彪), Wang Y-P(王一平), Yu X-Q(余新桥), Ying C-S(应存山), Li Z-K(黎志康). Molecular mapping of QTLs for rice milling yield traits. Acta Genet Sin (遗传学报), 2002, 29(9): 791–797 (in Chinese with English abstract)
[8]Septiningsih E M, Trijatmiko K R, Moeljopawiro S, McCouch S R. Identification of quantitative trait loci for grain quality in an advanced backcross population derived from Oryza sativa variety IR64 and the wild relative O. rufipogon. Theor Appl Genet, 2003, 107: 1433–1441
[9]Aluko G, Martinez C, Tohme J, Castano C, Bergman C, Oard J H. QTL mapping of grain quality traits from the interspecific cross Oryza sativa × O. glaberrima. Theor Appl Genet, 2004, 109: 630–639
[10]Dong Y J, Tsuzuki E, Lin D Z, Kamiunten H, Terao H, Matsuo M, Cheng S H. Molecular genetic mapping of quantitative trait loci for milling quality in rice (Oryza sativa L.). J Cereal Sci, 2004, 40: 109–114
[11]Zheng T Q, Xu J L, Li Z K, Zhai H Q, Wan J M. Genomic regions associated with milling quality and grain shape identified in a set of random introgression lines of rice (Oryza sativa L.). Plant Breed, 2007, 126: 158–163
[12]Eshed Y, Zamir D. An introgression line population of Lycopersicon pennellii in the cultivated tomato enables the identi?cation and ?ne mapping of yield-associated QTL. Genetics, 1995, 141: 1147–1162
[13]Li Z K, Fu B Y, Gao Y M, Xu J L, Ali J, Lafitte R, Jiang Y Z, Domingo-Rey J, Vijayakumar C H M, Dwivedi D, Maghirang R, Zheng T Q, Zhu L H. Genome-wide introgression lines and their use in genetic and molecular dissection of complex phenotypes in rice (Oryza sativa L.). Plant Mol Biol, 2005, 59: 33–52
[14]Temnykh S, Park W, Ayres N, Cartinhour S, Hauck N, LipovichL, Cho Y G, Ishii T, McCouch S R. Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.). Theor Appl Genet, 2000, 100: 697–712
[15]McCouch S R, Teytelman L, Xu Y, Lobos K B, Clare K, Walton M, Fu B, Maghirang R, Li Z, Xing Y, Zhang Q, Kono I, Yano M, Fjellstrom R, DeClerck G, Schneider D, Cartinhour S, Ware D, Stein L. Development of 2 240 new SSR markers for rice (Oryza sativa L.). DNA Res, 2002, 9: 199–207
[16]Yang J, Hu C C, Hu H, Yu R D, Xia Z, Ye X Z, Zhu J. QTL Network: mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics, 2008, 24: 721–723
[17]Guo Y-M(郭咏梅), Mu P(穆平), Liu J-F(刘家富), Lu Y-X(卢义宣), Li Z-C(李自超). Comparative studies on quality characters under water- and dry-cultivation in rice. Acta Agro Sin (作物学报), 2005, 31(11): 1443–1448 (in Chinese with English abstract)
[18]Mu P(穆平), Guo Y-M(郭咏梅), Liu J-F(刘家富), Lu Y-X(卢义宣), Li Z-C(李自超). QTL mapping and QTL × environments interactions of grain milling and appearance quality traits in rice under upland and lowland environments. J Agric Biotechnol (农业生物技术学报), 2007, 15(4): 654–660 (in Chinese with English abstract)
[19]Weng J-F(翁建峰), Wan X-Y(万向元), Guo T(郭涛), Jiang L(江玲), Zhai H-Q(翟虎渠), Wan J-M(万建民). Stability analysis of QTL for milling quality of rice (Oryza stativa L.) using CSSL population. Sci Agric Sin (中国农业科学), 2007, 40(10): 2128–2135 (in Chinese with English abstract)
[20]Li Z F, Wan J M, Xia J F, Zhai H Q, Ikehashi H. Identification of quantitative trait loci underlying milling quality of rice (Oryza sativa) grains. Plant Breed, 2004, 123: 229–234

相关文章 15

[1]	刘秋员, 周磊, 田晋钰, 程爽, 陶钰, 邢志鹏, 刘国栋, 魏海燕, 张洪程. 长江中下游地区常规中熟粳稻产量、品质及氮素吸收性状的相互关系分析[J]. 作物学报, 2021, 47(5): 904-914.
[2]	韩展誉,管弦悦,赵倩,吴春艳,黄福灯,潘刚,程方民. 灌浆温度和氮肥及其互作效应对稻米贮藏蛋白组分的影响[J]. 作物学报, 2020, 46(7): 1087-1098.
[3]	苏达,吴良泉,Søren K. Rasmussen,周庐建,潘刚,程方民. 磷营养对水稻籽粒锌生物有效性的影响及其与植酸等磷酸肌醇谱含量的关系[J]. 作物学报, 2020, 46(02): 228-237.
[4]	唐健,唐闯,郭保卫,张诚信,张振振,王科,张洪程,陈恒,孙明珠. 氮肥施用量对机插优质晚稻产量和稻米品质的影响[J]. 作物学报, 2020, 46(01): 117-130.
[5]	赵小强,任斌,彭云玲,徐明霞,方鹏,庄泽龙,张金文,曾文静,高巧红,丁永福,陈奋奇. 8种水旱环境下2个玉米群体穗部性状QTL间的上位性及环境互作效应分析[J]. 作物学报, 2019, 45(6): 856-871.
[6]	韩超,许方甫,卞金龙,徐栋,裘实,赵晨,朱盈,刘国栋,张洪程,魏海燕. 淮北地区机械化种植方式对不同生育类型优质食味粳稻产量及品质的影响[J]. 作物学报, 2018, 44(11): 1681-1693.
[7]	吕品, 于海峰, 侯建华. 利用抗旱选择导入系定位向日葵产量性状QTL[J]. 作物学报, 2018, 44(03): 385-396.
[8]	沈超,李定国,聂以春,林忠旭. 利用黄褐棉染色体片段导入系定位产量和纤维品质性状QTL[J]. 作物学报, 2017, 43(12): 1733-1745.
[9]	朱协飞,王鹏,司占峰,张天真*. 基于陆地棉背景的海岛棉染色体片段导入系产量性状QTL定位[J]. 作物学报, 2017, 43(12): 1784-1790.
[10]	陈梦云,李晓峰,程金秋,任红茹,梁健,张洪程,霍中洋. 秸秆全量还田与氮肥运筹对机插优质食味水稻产量及品质的影响[J]. 作物学报, 2017, 43(12): 1802-1816.
[11]	毛艇,李旭,李振宇,徐正进. 水稻Wx复等位基因基于PCR的功能标记开发与利用[J]. 作物学报, 2017, 43(11): 1715-1723.
[12]	胡群,夏敏,张洪程,曹利强,郭保卫,魏海燕,陈厚存,韩宝富. 氮肥运筹对钵苗机插优质食味水稻产量及品质的影响[J]. 作物学报, 2017, 43(03): 420-431.
[13]	闫伟,李元,宋茂兴,张旷野,孙铭泽,瞿会,李凤海,钟雪梅,朱敏,杜万里,吕香玲*. 玉米抗灰斑病QTL元分析及其验证[J]. 作物学报, 2016, 42(05): 758-767.
[14]	彭少兵. 转型时期杂交水稻的困境与出路[J]. 作物学报, 2016, 42(03): 313-319.
[15]	田青兰,李培程,刘利,张强,任万军. 四川不同生态区高产栽培条件下的杂交籼稻的稻米品质[J]. 作物学报, 2015, 41(08): 1257-1268.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed